A growing number of common genetic variants have been robustly and reproducibly associated with type 2 diabetes (T2D). Despite these advances, the precise identity of the genes involved in increasing T2D risk has not yet been established. The newly developed Metabochip supports genotyping of ~200,000 single nucleotide polymorphisms (SNPs) that display robust evidence for association with diseases and traits relevant to metabolic endpoints, as well as detailed fine-mapping of loci already validated at genome-wide statistical significance. We propose to deploy this array in the Diabetes Prevention Program (DPP), a clinical trial whose strengths include the enrollment of high-risk participants from multiple ethnic groups, exquisite longitudinal phenotyping, the presence of behavioral and pharmacologic interventions, and ongoing monitoring with additional accrual of hard endpoints. We will leverage the exquisitely phenotyped DPP samples to 1) test the association of select Metabochip SNPs with baseline T2D-related quantitative traits in 3,548 DPP participants at high risk of diabetes from five ethnic groups;2) assess the effect of select Metabochip SNPs on the incidence of metabolic outcomes in the DPP, and establish whether a lifestyle intervention modifies this risk;and 3) examine the impact of metformin and troglitazone on relevant SNPs, as a way to place them on metabolic pathways and describe potentially useful pharmacogenetic interactions. If successful, this proposal should help clarify the pathophysiologic mechanisms by which genetic variants increase risk of T2D, assess their impact on interventions to prevent T2D, generate a unique resource, and help lay the groundwork for pharmacogenetic and genetically-guided lifestyle intervention trials. PUBLIC HEALTH RELEVANCE: Recent studies have identified a growing number of common genetic variants that are reproducibly associated with type 2 diabetes and related traits. A newly developed genotyping array (the Metabochip) supports genotyping of ~200,000 single nucleotide polymorphisms that display robust evidence for association with diseases and traits relevant to metabolic endpoints, as well as detailed fine-mapping of validated genetic loci. We propose to deploy this array in the Diabetes Prevention Program (DPP), a clinical trial which enrolled 3,819 high-risk participants from multiple ethnic groups and randomized them to placebo, metformin, troglitazone or a lifestyle intervention to prevent diabetes. In the DPP, we will test the association of select variants with baseline diabetes-related quantitative traits, incidence of metabolic outcomes, response to the lifestyle intervention, and the effects of metformin and troglitazone.